Predictive Maintenance, or PdM, programs in industrial plants are frequently implemented by assigning a technician to use portable instrumentation, such as a vibration analyzer, an ultrasonic gun, and/or an IR camera, along a predetermined route to collect data related to the operation of the equipment on this route. This information, in turn, may then be used to diagnose problems or potential problems associated with the health and/or operation of the equipment, and to predict equipment availability.
For example, a PdM program may include a technician, i.e., operator carrying a vibration analyzer device to each machine located along a defined route. Upon reaching a particular machine that desired to be analyzed, a vibration sensor, such as an accelerometer, is physically coupled to the machine at one or more measurement locations. Specific measurements are acquired at each location on the machine as specified in the route instructions. The vibration sensor and analyzer then receive vibration data from the measurement locations, and may output this information on a display of the analyzer. Once the information on all machines on the route has been collected, this information is transferred to a host workstation which contains the entire database and the analysis software.
Most PdM programs are conducted by a team of a few individuals. The key functions to be performed are data collection and data analysis resulting in a status report identifying healthy machines and those in need of maintenance. In many cases, the same person may perform both functions, and in larger plants, program personnel will be assigned to different areas of the plant to provide coverage for all machines in the program. In other cases, one or more technicians may perform all of the data collection and other individuals may perform the analysis/reporting function. In either case, the individuals are typically in close proximity to each other, sometimes in the same office. If the analyst desires to inspect the machine or collect additional data to be more certain of his diagnosis, then he would typically travel to the location of the machine to perform more in depth troubleshooting. Many practitioners in the industry will not allow others to perform data collection for the machines that they must analyze because they believe that information picked up by the five senses when you are at the machine will not be effectively communicated back to them and that the technicians will not know when or how to collect more sophisticated measurements that could be needed to isolate the fault condition. Quality of remote analysis can be greatly improved when verifiable observations from the field are included with routinely collected data. Although this need for close communication between the analyst and the data collector is recognized, it has typically been handled by face-to-face verbal exchanges or text field notes attached to the route data.
The scheduling of both data collection and data analysis is also handled by word-of-mouth methods when the PdM personnel are located in close proximity to each other. It is common for vibration data to be collected periodically, for example once per month; however, equipment and personnel availability may cause the timing of the collection task to vary each month or even be omitted. Clearly, analysis cannot begin until data has been collected. As might be expected, the exchange of this information is typically handled verbally or via emails between team members.
Another important communication exchange should occur between the analyst and the maintenance planner. The analyst will commonly prepare a report which identifies machines in need of correction or maintenance. In many cases, the planner will have months of forewarning during which he can schedule work orders to be performed. The planner should schedule the maintenance actions in such a way as to minimize the impact of these repairs on the production of the plant. Thus, in many cases, an analyst may call a problem at a very early stage of degradation and track it for several months before a repair is performed. It is important to verify that the maintenance performed on the machine has corrected the problem. Further, it is important to know whether the faults that were identified were correct and if not, what was the fault condition discovered. It is also important to attempt to document the root cause of the fault which may be determined from an inspection of the damage parts removed from the machine or machine conditions noted during the removal process. It is common practice for this communication exchange to occur via verbal exchanges or emails; however, the occurrence and fidelity of this exchange is often compromised by departmental priorities, physical separation, and the significant time delay which may occur between the identification and the correction of the fault.
When PdM programs were executed by small teams in close proximity to each other, the ad hoc communication methods were adequate. However, a new model for PdM programs has been developed which offers significant opportunities to improve the effectiveness and to reduce the cost of executing these programs. The new model utilizes a geographically diverse staff that relies upon the internet to communicate data and information between team members. There are many factors important to executing and sustaining a PdM program in a plant; however, one of the hardest factors to manage and maintain is the need for diagnostic expertise. A skilled analyst typically takes a number of years to learn his trade and the pool of those with this skill is in diminishing supply. Bringing the data to the analysts, rather than bringing the analysts to the machines, can improve the effectiveness and reduce the overall cost of these programs.